Customer Story: Riot Games | Databricks

Innovative performance gains improve the gaming experience

Through data processing and data science productivity improvements, Riot Games has been able to deliver on several use cases to ensure a better gaming experience. Most notably, through the use of Delta Lake, the processing performance for ETL is 50% faster than with EMR — significantly speeding up innovation. With data flowing freely downstream, the Riot Games recommendation engine maps over 120 types of characters and across multiple unique skins, totaling thousands of different combinations and billions of gameplay data points. Gamers can now more easily find the content they want, which is driving Riot Games conversions.

Databricks enabled the Riot Games data team to build and deploy a prediction model for gameplay lag caused by network delays. The streaming architecture delivers real-time anomaly detection with network operation alerts. Now, Riot Games can preemptively solve issues before negatively impacting players, thereby elevating the in-game experience. Root cause insights are incredibly accurate, and network performance overall has substantially improved due to the constant stream of new data being ingested into the model.

Because Databricks integrates with the latest deep learning frameworks, such as TensorFlow, Riot Games has also been able to develop and train deep learning models with ease. Today, Riot Games can understand and detect abusive language during gameplay, in real-time. As a result, they can isolate the “bad apples” with consequences to reduce abusive behavior throughout the game. The more appropriate environment has increased customer satisfaction, retention and lifetime value, thereby contributing to the overall in-game experience. Riot Games will continue utilizing the Databricks Lakehouse Platform to empower and enable data scientists and engineers as they continue to capitalize on new and innovative opportunities to improve the gamer experience in League of Legends.